Optimal planning of trip and round trip cycle time on an urban route

Authors

DOI:

https://doi.org/10.15587/2312-8372.2018.129039

Keywords:

urban public transport, waiting time, trip duration, generalized expenses

Abstract

The object of research is the public urban passenger transport route. One of the most problematic places in the organization of transportation on a fixed city route is the establishment of the planned trip duration and/or round trip. Difficulties arise because the trip duration on a city route is usually a random variable, which must be taken into account when establishing its planned values, used later when scheduling traffic. This, on the one hand, makes it possible to increase the efficiency of the use of route vehicles by reducing their unproductive outages, and on the other hand, to improve the quality of passenger service by reducing the waiting time for the last transport at stops.

During the research, the method of stochastic optimization of the planned trip duration is used. This makes it possible to find a compromise in terms of value between the efficiency of using route vehicles and the quality of passenger service. A feature of the proposed optimization method is the consideration in the generalized costs of unproductive idle times of route vehicles, the lost profit of the transport operator and the cost of transport time for passengers.

The application of the developed method for the conditions of the trolleybus route No. 14 of the city of Zaporizhzhia (Ukraine) allows, in comparison with the existing planned indicators, to reduce the total costs by 12 %.

Now the technical possibilities of collection, accumulation and processing of empirical information on the conditions for performing transportation on urban routes using satellite systems of global GPS positioning have significantly expanded. In such conditions, using the developed method, it is possible to take operational account of the operational and socio-economic factors in the planning of passenger traffic in which these transportations are carried out.

Author Biography

Olexiy Kuzkin, Zaporizhzhia National Technical University, 64, Zhukovskogo str., Zaporizhzhia, Ukraine, 69063

PhD, Associate Professor

Department of Transport Technologies

References

  1. Ceder, A. (2007). Public transit planning and operation: theory, modeling and practice. Oxford: Elsevier. Butterworth-Heinemann, 626.
  2. Spirin, I. V. (2004). Perevozki passazhirov gorodskim transportom. Moscow: IKTS «Akademkniga», 413.
  3. Kuzkin, О. F. (2015). Service regularity investigation of fixed-route taxi during on-peak hours. Eastern-European Journal of Enterprise Technologies, 5 (3 (77)), 14–22. doi:10.15587/1729-4061.2015.51361
  4. Babushkin, H. F., Kuzkin, O. F., Yudin, V. P. (2010). Transportno-ekolohichni problemy mista Zaporizhzhia. Novi materialy i tekhnolohii v metalurhii ta mashynobuduvanni, 1, 144–146.
  5. Artynov, A. P., Skaletskiy, V. V. (1981). Avtomatizatsiya protsessov planirovaniya i upravleniya transportnymi sistemami. Moscow: Nauka, 280.
  6. Larin, O. N. (2005). Organizatsiya passazhirskikh perevozok. Chelyabinsk: YUUrGU, 104.
  7. Efremov, I. S., Kobozev, V. A., Yudin, V. A. (1980). Teoriya gorodskikh passazhirskikh perevozok. Moscow: Vysshaya shkola, 535.
  8. Ryusk, P., Vandehey, M., Elefteriadou, L. et al. (2011). Highway capacity manual 2010. TR News, 273. Washington D.C.: Transportation Research Board, National Research Council, 45–48.
  9. Islam, M. K. (2010). Reliability Analysis of Public Transit Systems Using Stochastic Simulation. World Transit Research. Canberra, 13.
  10. Transit Capacity and Quality of Service Manual: TRCP Report 165. (2013). Washington D.C.: Transportation Research Board, 685. doi:10.17226/24766
  11. Ibarra-Rojas, O. J., Delgado, F., Giesen, R., Munoz, J. C. (2015). Planning, operation, and control of bus transport systems: A literature review. Transportation Research Part B: Methodological, 77, 38–75. doi:10.1016/j.trb.2015.03.002
  12. Diab, E. I., El-Geneidy, A. M. (2013). Variation in bus transit service: understanding the impacts of various improvement strategies on transit service reliability. Public Transport, 4 (3), 209–231. doi:10.1007/s12469-013-0061-0
  13. El-Geneidy, A. M., Horning, J., Krizek, K. J. (2011). Analyzing transit service reliability using detailed data from automatic vehicular locator systems. Journal of Advanced Transportation, 45 (1), 66–79. doi:10.1002/atr.134
  14. Davidich, Yu. A., Kalyuzhnyy, M. V. (2012). Normirovanie skorosti dvizheniya gorodskogo passazhirskogo transporta s uchetom kharakteristik marshruta. Vіstі avtomobіl'no-dorozhn'ogo іnstitutu, 1 (14), 11–17.
  15. El-Geneidy, A., Hourdos, J., Horning, J. (2009). Bus Transit Service Planning and Operations in a Competitive Environment. Journal of Public Transportation, 12 (3), 39–59. doi:10.5038/2375-0901.12.3.3
  16. Wu, Y., Tang, J., Gong, J. (2015). Optimization Model for Single Bus Route Schedule Design Problem with Stochastic Travel Time. Journal of Northeastern University: Natural Science, 36 (10), 1393–1397. doi:10.3969/j.issn.1005-3026.2015.10.006
  17. Gong, X., Guo, X., Dou, X., Lu, L. (2015). Bus Travel Time Deviation Analysis Using Automatic Vehicle Location Data and Structural Equation Modeling. Mathematical Problems in Engineering, 2015, 1–9. doi:10.1155/2015/410234
  18. Mazloumi, E., Currie, G., Rose, G. (2010). Using GPS Data to Gain Insight into Public Transport Travel Time Variability. Journal of Transportation Engineering, 136 (7), 623–631. doi:10.1061/(asce)te.1943-5436.0000126
  19. Uno, N., Kurauchi, F., Tamura, H., Iida, Y. (2009). Using Bus Probe Data for Analysis of Travel Time Variability. Journal of Intelligent Transportation Systems, 13 (1), 2–15. doi:10.1080/15472450802644439
  20. Qu, X., Oh, E., Weng, J., Jin, S. (2014). Bus travel time reliability analysis: a case study. Proceedings of the Institution of Civil Engineers – Transport, 167 (3), 178–184. doi:10.1680/tran.13.00009
  21. Acosta, C., Gallagher, S., Laberge, M., Townsend, M. (2011). Transit System Analysis and Optimization in Montgomery County. Worcester: Worcester Polytechnic Institute, 86.
  22. Improving Bus Transit On-Time Performance through the Use of AVL Data (final). (2014). Pascal Systems Inc. Latham, 28.
  23. Sahoo, P. (2013). Probability and mathematical statistics. Louisville: University of Louisville, 686.
  24. Kobzar, A. I. (2006). Prikladnaya matematicheskaya statistika. Dlya inzhenerov i nauchnykh rabotnikov. Moscow: FIZMATLIT, 816.
  25. Chetchuev, M. V., Kostenko, V. V., Fedorov, V. P., Homich, D. I. (2014). Faktor skorosti kak ekonomicheskaya kategoriya passazhirskikh transportnykh sistem v gorodskikh aglomeratsiyakh. Magnitolevitatsionnye transportnye sistemy i tekhnologii. Saint Petersburg, 205–211.
  26. Mackie, P. J., Jara-Diaz, S., Fowkes, A. S. (2001). The value of travel time savings in evaluation. Transportation Research Part E: Logistics and Transportation Review, 37 (2-3), 91–106. doi:10.1016/s1366-5545(00)00013-2
  27. Holovne upravlinnia statystyky v Zaporizkii oblasti. Available at: http://www.zp.ukrstat.gov.ua/. Last accessed: 08.03.2018.
  28. Zhao, J., Dessouky, M., Bukkapatnam, S. (2006). Optimal Slack Time for Schedule-Based Transit Operations. Transportation Science, 40 (4), 529–539. doi:10.1287/trsc.1060.0170

Published

2017-12-28

How to Cite

Kuzkin, O. (2017). Optimal planning of trip and round trip cycle time on an urban route. Technology Audit and Production Reserves, 2(2(40), 34–42. https://doi.org/10.15587/2312-8372.2018.129039

Issue

Section

Information Technologies: Original Research